Intelligent systems may be viewed as a framework for solving the problems of nonlinear system control. The intelligence of the system in the nonlinear or changing environment is used to recognize in which environment the system currently resides and to service it appropriately. This paper presents a general methodology of adaptive control based on multiple models in fuzzy form to deal with plan...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

This paper describes a new metaheuristic for combinatorial optimisation problems with specific reference to the jobshop scheduling problem (JSP). A fuzzy greedy search algorithm (FGSA) which is a combination of a genetic algorithm (GA) and a greedy randomised adaptive search procedure (GRASP) is considered to solve the problem. The effectiveness and efficiency of the proposed hybrid method will...

Soft computing techniques proved to be successful in many application areas. In this paper we investigate the application in psychopathological field of two well known soft computing techniques, fuzzy logic and genetic algorithms (GAs). The investigation started from a practical need: the creation of a tool for a quick and correct classification of mental retardation level, which is needed to c...

This paper introduces a methodology for soil slope stability analysis based on optimization, limit equilibrium principles and method of slices. In this study, the slope stability analysis problem is transformed into a constrained nonlinear optimization problem. To solve that, a Self-Adaptive Genetic Algorithm (GA) is utilized. In this study, the slope stability safety factors are the objective ...

The paper contains a discussion material and preliminary experimental results on a new approach to building on-line, adaptive decision making and control systems. This approach is called evolving connectionist systems (ECOS). ECOS evolve through incremental, on-line learning. They can accommodate any new input data, including new features, new classes, etc. New connections and new neurons are c...

Fuzzy Neural Networks (FNNs) techniques have been effectively used in applications that range from medical to mechanical engineering, to business and economics. Despite of attracting researchers in recent years and outperforming other fuzzy systems, Adaptive Neuro-Fuzzy Inference System (ANFIS) still needs effective parameter training and rulebase optimization methods to perform efficiently whe...

This paper presents a Fuzzy Simulated Evolution algorithm for VLSI standard cell placement with the objective of minimizing power, delay and area. For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. Approximation iterative heuristics such as Simulated Evolution are best...

An adaptive predictive control methodology is applied for a fossil fuel boiler control. The control algorithm takes advantage of a neuro-fuzzy identifier system for prediction of the boiler response in a future time window. An optimizer algorithm based on evolutionary programming technique (EP) uses the identifier-predicted outputs and determines input sequence in a time window. The present opt...